### Abstract

Original language | English |
---|---|

Place of Publication | Tilburg |

Publisher | Operations research |

Number of pages | 15 |

Volume | 2006-86 |

Publication status | Published - 2006 |

### Publication series

Name | CentER Discussion Paper |
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Volume | 2006-86 |

### Fingerprint

### Keywords

- hierarchical forecasting
- aggregation
- top-down approach

### Cite this

*Hierarchical Estimation as Basis for Hierarchical Forecasting*. (CentER Discussion Paper; Vol. 2006-86). Tilburg: Operations research.

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**Hierarchical Estimation as Basis for Hierarchical Forecasting.** / Strijbosch, L.W.G.; Heuts, R.M.J.; Moors, J.J.A.

Research output: Working paper › Discussion paper › Other research output

TY - UNPB

T1 - Hierarchical Estimation as Basis for Hierarchical Forecasting

AU - Strijbosch, L.W.G.

AU - Heuts, R.M.J.

AU - Moors, J.J.A.

N1 - Subsequently published in IMA Journal of Management Mathematics, 2008 (rt) Pagination: 15

PY - 2006

Y1 - 2006

N2 - In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items.Since HF is a complicated procedure, analytical results are hard to obtain; consequently, most literature is based on simulations and case studies.This paper succeeds in following a more theoretical approach by simplifying the problem : we consider estimation instead of forecasting.So, from a random sample we estimate both total demand and the fraction of this total that individual items take; multiplying these two quantities gives a new estimate of individual demand.Then our research question is: can aggregation of items, followed by fractioning, lead to more accurate estimates of individual demand?Thirdly, a more practical situation is investigated by means of simulation.

AB - In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items.Since HF is a complicated procedure, analytical results are hard to obtain; consequently, most literature is based on simulations and case studies.This paper succeeds in following a more theoretical approach by simplifying the problem : we consider estimation instead of forecasting.So, from a random sample we estimate both total demand and the fraction of this total that individual items take; multiplying these two quantities gives a new estimate of individual demand.Then our research question is: can aggregation of items, followed by fractioning, lead to more accurate estimates of individual demand?Thirdly, a more practical situation is investigated by means of simulation.

KW - hierarchical forecasting

KW - aggregation

KW - top-down approach

M3 - Discussion paper

VL - 2006-86

T3 - CentER Discussion Paper

BT - Hierarchical Estimation as Basis for Hierarchical Forecasting

PB - Operations research

CY - Tilburg

ER -